AI/AR and Machine Learning


New opportunities for early-adopting manufacturers

Cloud computing, big data, augmented reality and artificial intelligence (AI) are opening up new opportunities for early-adopting manufacturers seeking to create smarter machines and processes.  Zuken has ongoing R&D programs focused on developing new applications leveraging latest advancements in these areas. Using the 3D models generated by our design and engineering tools, we expect to be able to offer users the chance to visualise their product in an augmented reality environment before handing them over for manufacturing.



Virtual and Augmented Reality for Wire Harness Design

E3.Harness Analyzer is our first product that offers an immersive experience for viewing KBL-based automotive wiring harnesses in augmented reality. This world-first AR harness digital twin was launched at the Automotive Wire Harness Conference in March 2018 in Germany.

Revolutionizing PCB Design: Discover Zuken’s AI-Enhanced CR-8000 Platform

Zuken introduces a groundbreaking approach to PCB design with its AI-driven CR-8000 platform. This platform incorporates artificial intelligence to revolutionize PCB design, offering a unique three-stage deployment of AI-based products. These include Basic Brain, leveraging Zuken’s extensive design library; Dynamic Brain, learning from users’ past designs; and Autonomous Brain, continuously advancing with each project. This AI integration aims to streamline the design process, enhancing efficiency, creativity, and productivity in PCB design.

AI in PCB Design

AI for PCB Design: AI in PCB Design Process


Artificial Intelligence and Machine Learning for PCB Design

Machine learning offers significant opportunities for solving routing and component placement challenges in PCB design. Current R&D approaches include setting up an automatic system for self-learning, as in the Deep Mind project AlphaGo Zero. We are evaluating how to measure routing success, since human opinion on the most superior routing solution for any given situation can differ widely. Neural networks offer a way of classifying data being presented to the routing system – one of the greatest challenges to creating a robust machine learning environment.

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